# 向后传递

`feedforward()`实现向后传递的功能。

向后传递的公式：

$$
a' = \sigma (w a + b)  \\
\sigma(z) = \frac{1}{1+\exp(-z)}
$$

w和b为某个神经上的参数，a为上层的输出，a'为这个神经元的输出。

```python
def feedforward(self, a):
    """Return the output of the network if "a" is input."""
    for b, w in zip(self.biases, self.weights):
        a = sigmoid(np.dot(w, a)+b)
    return a

def sigmoid(z):
    return 1.0/(1.0+np.exp(-z))
```

sigmoid函数用于实现$$\sigma(z)$$，需注意的是入参z是一个向量。\
sigmoid函数是对整个向量计算的。


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